This project?s long-term goal is to develop the Dietary Data Monitoring Platform (DDMP): an integrated, scalable system for both clinical and research applications that collects and manages data on an individual?s food intake. DDMP is designed to reduce the burden of collecting multilpe-day records of food intake, improve the accuracy of serving size measurement, and streamline the processes of patient/participant training, scheduling and data processing. The Phase II effort will beta test and finalize DDMP during a series of validation studies. During beta testing, the interface, software, and reporting tools developed in Phase I will be reevaluated for clinical and research applications. Linkages to the NSDR, FNDDS, MPED, and the Gladson Nutritional Database will be used to estimate the energy and nutrient intake associated with the reconstructed food volume. DDMP will utilize a high throughput, low latency data collection framework and intuitive reporting system. The database will utilize cloud computing and storage for remote access, providing much needed improvement over disparate data collection platforms used clinically and in health-related studies. This will enable more efficient nutrition intervention in clinical settings and make possible several types of research designs (e.g., case-cohort studies) that are unfeasible using paper food records.